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A little game I've been playing lately is that if I'm listening to a band whose social media profile I have not seen, I try to guess how many followers/fans they have. I am very bad at this game, because twice I've been listening to certain pop-punk bands and I've thought "These guys are pretty good, but they also seem kind of niche, so I'm going to guess that they have about 15,000 followers/fans. Yeah, that seems about right." And both times, I was completely wrong, and they had like 100,000 followers/fans. So this week, I have learned that much like you can't judge a book by its cover or a hitter by his line drive percentage, you can't judge a band's social media presence by its sound.

Monday

How good a catcher is at framing has absolutely nothing to do with how tall he is, and it doesn't have much to do with how old he is, either: Catcher Framing: Does Size Matter, And Is Age Just a Number?, by Shane Tourtellotte, The Hardball Times

One can also, with some long formulas, weight the trendline produced by the data. Instead of catchers gaining about three extra strikes per 1,000 pitches for each inch they gain, as you’d get with the Telis outlier, they lose around an eighth of a strike per 1,000 for each added inch.

At least they do until you calculate the (weighted) r^2 value: 0.0022. The actual correlation is next to zero. Catcher height has effectively nothing to do with framing ability.

As a check, I ran the numbers with the Baseball Prospectus data and got very similar results despite their being more lenient toward Telis’ poor framing. Both the change in extra strikes for height and the r^2 value were so low, they are for all practical purposes zero.

Tuesday

Everybody loves the Area Code Games! Except the guys who do really poorly there, I guess. They probably don't like it too much: Area Code Games Impressions, by Chris Crawford, Baseball Prospectus

“It’s my favorite tournament,” an AL scouting director told me. “You just don’t get a chance to see first round picks on the same field for multiple days very often, and you see that every year here. The regular season means more, but an awful lot of money can be made during tournaments like this.”

Throwing a position player with a huge lead wouldn't be unadvisable at all. Somebody just do it already!: What about position players pitching with a huge lead, by Zachary Levine, Baseball Prospectus

Of course, this is assuming that the manager would be sitting on his hands watching and hoping for the hitter to hit it at somebody. In reality, when it reached a certain critical point, he’d certainly start to get a real reliever ready and at some other point, use that guy he would have used anyway.So if a team is up by 13, there’s a 1 in 775 chance that the other team would, not even win, but just come back to tie.

So let’s say the team decides that if the lead ever shrinks to five – or more precisely if they were in a situation where if everyone on the bases scored, the lead would shrink to five – that they’d bring in the real reliever. The win probability for a team pitching the bottom of the ninth with a five-run lead fluctuates year-to-year but generally dances around 99 percent. So we can redo that table in two parts, where the trailing team needs to both get the deficit down to five and then come back from down five against the reliever (we’ll even be overly conservative again and assume no outs were recorded to get the 99 percent).

Contact data is a pretty strong predictor of a player's success…on a season-long scale. On a season-by-season basis, it's pretty useless: Offensive Batted Ball Statistics and Their Uses, by Bradley Woodrum, The Hardball Times

These correlations suggest there is a strong relationship between a player’s BIS hit data and his ISO and SLG. But this is among qualified hitters from 2002 through half of 2015. These are big samples.

On the season level, the connection is much weaker. Looking at just the 2014 season, Soft%, Med%, and Hard% regress against ISO with a 0.56 R2—, and in all cases our P-values are less than great (if that’s a thing you care about), suggesting these aren’t the variables we’re looking for. (I, for one, don’t care much for P-values and definitely don’t pay much mind to arbitrary levels of statistical significance.)

Wednesday

The historically low walk rate in 2015 has his young players the worst: When A Young Man Walks By, by Matthew Trueblood, BP Wrigleyville

That 8.8-percent walk rate by young players is the fourth-best in baseball this year, and the three teams with higher rates for that age group (the Pirates, Nationals, and Dodgers) have combined for one fewer plate appearance than the Cubs alone have.

In fact, given the volume of playing time we’re talking about, the Cubs’ young hitters are drawing walks at an historic rate. Since 1969, 356 teams have allotted at least 2,000 plate appearances to players in that age bracket. These Cubs rank 95th in walk rate among those teams, putting them in the 73rd percentile. That’s impressive, but it doesn’t begin to really tell the story here.

Thursday

tOPS+ against relievers is at a historically low level: Reliever domination is at a historical level, by Chris Teeter, Beyond the Box Score

Each of the last five seasons (2011-2015) appear on this 'leaderboard'. In fact, save 2010, in which batters had decent success against relievers (97 tOPS+), each of the last ten seasons are found on the wrong end of this performance spectrum. I must note that the 2015 sample is limited as it is not a complete season, but thus far the performance is right in line with what we have seen of late. It is tied for the second lowest mark since 1975. We really are in an interesting strategic point in the history of the game. Relievers are being used more often, for shorter and shorter stints, which is perhaps contributing to them throwing harder and harder, and it is dampening offensive output.

Park factors can vary by the angles of fly balls, as well: The Fly-Ball/Line-Drive Park Factor, by Tony Blengino, Fangraphs

Taking a closer look at the table above, 23 of 30 clubs had FLY/LD park factors of above or below 100 in both 2014 and 2015. In addition, the higher of the FLY or LD park factors was the same for 23 of 30 clubs in both 2014 and 2015. There are hitter’s parks which inflate production on both fly balls and liners, and there are pitcher’s parks which deflate production on both. In addition, there are parks which inflate/deflate production on fly balls much more so than on liners. In other words, there are ballparks that are particularly fly-ball or line-drive friendly, or even ballparks that are more conducive to relatively high or low fly balls. Many fitting into the latter category are classified as liners by Statcast. This is quite important when you are evaluating a player for acquisition; a high exit angle guy like, say, Chris Carter is much more productive in Houston than he would be in say, St. Louis, where line-drive power is of much greater relative value.

Friday

Platoon splits isn't as simple at a something-handed pitcher throwing against a something-handed hitter, and lineup construction seems to ignore that fact: Forecasting Pitcher Platoon Splits, by Jared Cross, The Hardball Times

Managers, it appears, stack their lineups with more lefties when facing right-handed pitching but pay little attention to the projected platoon split of the pitcher. The right-handed pitchers projected to have reverse splits faced roughly as many left-handed batters as the right-handed pitchers with the most extreme projected splits and dramatically more left-handed batters than the left-handed pitchers with the weakest projected splits. Daily fantasy managers may well act similarly and, in either world, some advantage could be accrued by looking at more than just a pitcher’s throwing hand.

Thank you for reading

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